[olavgg]

I've already started, there is a bigger challenge though. That is, how do you sell this? I can think of plenty of scenarios for the oil and gas industry, which is the biggest industry where I live.

For example drilling for oil in sea is quite expensive, could easily cost over 100 million USD. With machine learning we can predict the seismic ground pattern by predicting the amount of clay, lime etc in different locations and between wells. This can help us to decide if there is a good chance there could be oil/gas underground.

The problem when I present this, is that it quickly sounds like science fiction.

[ajdecon]

Oil and gas already does a hell of a lot of computing, and invests heavily in supercomputing facilities. [0] I'm not too familiar with the domain, but looking at abstracts of conferences like the Oil & Gas HPC Workshop [1] might give you some idea of the work already being done in those fields.

It's entirely possible that machine learning techniques could be used as well as modeling and simulation for these problems. (They may be already! But my limited expose suggests they're mostly doing traditional HPC.) But you'd probably need to be a petroleum expert already, not just someone with machine learning expertise living in an O&G hub.[2]

[0] Just an example: http://www.aiche.org/chenected/2012/12/bp-building-new-houst...

[1] http://rice2014.og-hpc.org/

[2] Apologies, btw, if you are a petroleum expert who's just frustrated by a lack of machine learning in the industry. :)